Abstract

Despite the key role of magnetic resonance imaging (MRI) in the diagnosis and monitoring of multiple sclerosis (MS) and cerebral small vessel disease (SVD), the association between clinical and radiological disease manifestations is often only moderate, limiting the use of MRI-derived markers in the clinical routine or as endpoints in clinical trials. In the projects conducted as part of this thesis, we addressed this clinico-radiological gap using two different approaches. Lesion-symptom association: In two voxel-based lesion-symptom mapping studies, we aimed at strengthening lesion-symptom associations by identifying strategic lesion locations. Lesion mapping was performed in two large cohorts: a dataset of 2348 relapsing-remitting MS patients, and a population-based cohort of 1017 elderly subjects. T2-weighted lesion masks were anatomically aligned and a voxel-based statistical approach to relate lesion location to different clinical rating scales was implemented. In the MS lesion mapping, significant associations between white matter (WM) lesion location and several clinical scores were found in periventricular areas. Such lesion clusters appear to be associated with impairment of different physical and cognitive abilities, probably because they affect commissural and long projection fibers. In the SVD lesion mapping, the same WM fibers and the caudate nucleus were identified to significantly relate to the subjects’ cerebrovascular risk profiles, while no other locations were found to be associated with cognitive impairment. Atrophy-symptom association: With the construction of an anatomical physical phantom, we aimed at addressing reliability and robustness of atrophy-symptom associations through the provision of a “ground truth” for atrophy quantification. The built phantom prototype is composed of agar gels doped with MRI and computed tomography (CT) contrast agents, which realistically mimic T1 relaxation times of WM and grey matter (GM) and showing distinguishable attenuation coefficients using CT. Moreover, due to the design of anatomically simulated molds, both WM and GM are characterized by shapes comparable to the human counterpart. In a proof-of-principle study, the designed phantom was used to validate automatic brain tissue quantification by two popular software tools, where “ground truth” volumes were derived from high-resolution CT scans. In general, results from the same software yielded reliable and robust results across scans, while results across software were highly variable reaching volume differences of up to 8%.